The primary objective of this project is to develop reliable, safe and cost-effective ultrasonic techniques for improved medical imaging and early tumor detection. The proposed work is based on concepts which have proven to be effective in prior applications in detection of ultrasonic signals, namely, frequency diversity and wavelet techniques. The primary objective is to improve detection of tumors, particularly at the early stages, which is both highly desirable and extremely challenging. Preliminary results from the application of these principles to medical images obtained from the breast and liver are highly encouraging and justify further research efforts. The various SSP algorithms significantly increased the contrast between the tumorous regions and the surrounding normal tissue, enabling easier identification of small cysts and lesions. In the proposed work, Constant-Q filtering and Wavelets will be used for signal decomposition and image enhancement. These are natural generalizations to SSP which provide added flexibility to employ non-Gaussian filter-banks designed for prescribed dual localization in time and frequency domains. The performance of all the algorithms will be evaluated with respect to conventional image processing methods.